Measurement of visual quality is of fundamental importance to some image processing applications

so an efficient image quality assessment algorithm is greatly needed.And the evaluation results of the conventional algorithms do not match to the ones of human vision because those algorithms ignore the characteristic of the Human Visual System (HVS) .According to the HVS that human have strong sensitivity to the image edge information

this paper propose a novel algorithm for image quality assessment based on the edge and background similarity between the distorted image and the reference (perfect) image.We test the validation of the proposed algorithm on the database of 779 images with five different distortion types

the results show our method has better performance than PSNR

MSSIM

IFC and VIF

because the evaluation results are closer to the ones of human vision.